week3 PRINCE GEORGE heat wave analysis
2024-05-20
Data
overview
## x y LOCAL_DATE TOTAL_PRECIPITATION
## Min. :-122.7 Min. :53.88 Length:29571 Min. : 0.000
## 1st Qu.:-122.7 1st Qu.:53.89 Class :character 1st Qu.: 0.000
## Median :-122.7 Median :53.89 Mode :character Median : 0.000
## Mean :-122.7 Mean :53.89 Mean : 1.603
## 3rd Qu.:-122.7 3rd Qu.:53.89 3rd Qu.: 1.600
## Max. :-122.7 Max. :53.89 Max. :50.000
## NA's :223
## STATION_NAME MAX_TEMPERATURE MIN_TEMPERATURE TOTAL_RAIN
## Length:29571 Min. :-36.900 Min. :-50.000 Min. : 0.000
## Class :character 1st Qu.: 2.000 1st Qu.: -6.100 1st Qu.: 0.000
## Mode :character Median : 10.000 Median : -0.400 Median : 0.000
## Mean : 9.441 Mean : -1.775 Mean : 1.134
## 3rd Qu.: 18.300 3rd Qu.: 5.400 3rd Qu.: 0.400
## Max. : 37.900 Max. : 20.700 Max. :50.000
## NA's :78 NA's :62 NA's :4989
## MIN_REL_HUMIDITY
## Min. : 11.00
## 1st Qu.: 37.00
## Median : 51.50
## Mean : 53.09
## 3rd Qu.: 69.00
## Max. :100.00
## NA's :21167## x y LOCAL_DATE TOTAL_PRECIPITATION
## 0 0 0 223
## STATION_NAME MAX_TEMPERATURE MIN_TEMPERATURE TOTAL_RAIN
## 0 78 62 4989
## MIN_REL_HUMIDITY
## 21167check wrangling data
check temp dist for in a random day from all year value
## [1] 6.7 7.8 12.2 7.8 5.0 5.6 4.4 3.9 4.4 5.0 7.8 8.9
## [13] 8.9 6.1 9.4 3.9 1.7 -3.9 -2.8 -1.1 -0.6 5.6 10.6 12.8
## [25] 10.6 8.9 11.7 15.0 15.6 12.2 5.0 7.8 4.4 6.1 7.2 8.3
## [37] 4.4 6.1 6.7 5.0 6.1 7.2 4.4 6.7 6.7 8.3 8.3 6.7
## [49] 7.8 8.3 1.1 2.8 6.7 6.1 6.7 10.0 8.3 7.2 2.8 5.0
## [61] 8.9 6.7 8.3 8.9 8.3 7.8 11.7 12.2 13.9 10.0 10.0 5.0
## [73] 5.6 -2.2 -1.1 1.7 1.1 1.7 4.4 7.2 3.9 3.9 8.9 6.1
## [85] 4.4 7.2 1.7 -2.8 -4.4 -0.6 3.9 5.0 7.8 6.7 4.4 5.0
## [97] 3.3 3.9 3.9 6.1 7.2 6.1 7.8 8.9 11.7 6.7 7.8 13.9
## [109] 8.9 8.9 8.9 7.2 4.4 3.9 4.4 3.3 5.0 6.1 5.0 5.0
## [121] 4.4 1.7 7.8 5.6 9.4 4.4 5.0 7.2 6.1 7.2 9.4 13.3
## [133] 13.9 8.3 8.3 5.0 1.7 5.6 6.1 7.2 7.2 9.4 7.8 2.2
## [145] 3.3 2.8 4.4 5.6 2.8 10.0 4.4 5.6 5.0 11.1 5.0 7.2
## [157] 9.4 6.1 5.6 3.9 5.6 6.1 8.3 7.2 8.3 6.7 8.9 3.3
## [169] 5.6 -1.1 -4.4 -5.0 0.6 4.4 2.8 1.7 -10.0 -6.7 -5.0 1.7
## [181] -3.9 -7.8 -16.7 -11.1 -3.3 4.4 5.0 9.4 9.4 7.8 7.8 3.3
## [193] 6.1 5.0 6.7 5.6 8.3 6.1 4.4 6.1 2.8 5.6 5.6 7.8
## [205] 3.9 4.4 6.7 8.9 7.8 1.7 1.7 4.4 5.0 3.9 3.9 2.8
## [217] 5.6 8.3 6.1 8.3 5.6 8.9 8.9 6.7 5.6 -6.7 -1.7 3.3
## [229] 5.6 5.6 9.4 10.0 6.7 8.9 9.4 7.8 8.9 8.3 11.1 11.1
## [241] 7.8 3.9 5.0 8.3 5.6 10.0 6.1 6.7 6.1 7.8 11.1 8.3
## [253] 8.9 6.1 6.7 10.0 9.4 10.6 10.0 15.0 6.1 8.3 0.6 6.1
## [265] 7.2 7.8 7.8 12.2 11.1 18.3 6.7 2.8 8.9 8.9 10.0 9.4
## [277] 12.2 8.3 10.0 11.7 13.3 14.4 12.2 5.0 2.8 2.2 -0.6 5.0
## [289] 6.7 7.8 7.2 6.7 7.2 11.1 14.4 13.9 15.0 14.4 16.1 11.7
## [301] 0.6 5.0 5.6 5.6 6.1 9.4 9.4 5.6 0.6 -3.9 -1.7 5.0
## [313] 7.8 7.8 8.3 -4.4 -9.4 -8.3 -6.7 -1.1 1.7 4.4 10.0 13.9
## [325] 13.3 13.9 6.7 8.9 8.3 6.1 2.8 -1.7 -5.0 -5.0 -6.7 -5.6
## [337] -7.2 -3.3 -1.1 4.4 10.6 6.7 7.8 10.0 8.9 1.1 1.7 8.3
## [349] 6.7 11.7 12.8 10.0 13.3 15.0 9.4 6.7 9.4 10.0 11.7 16.1
## [361] 4.4 7.2 10.0 2.8 2.8 0.6 5.0 4.4 3.3 1.7 2.8 6.7
## [373] 11.7 9.4 6.7 10.6 14.4 9.4 8.3 5.6 7.8 6.7 5.0 5.0
## [385] 5.6 5.0 5.6 6.1 9.4 11.1 6.7 3.3 6.7 7.2 8.3 11.1
## [397] 8.9 8.9 10.0 13.3 11.1 10.6 7.2 7.2 13.3 4.4 6.1 8.9
## [409] 8.9 4.4 7.8 10.6 7.2 8.9 9.4 8.9 6.7 8.3 8.3 11.1
## [421] -2.8 0.0 -1.1 -2.2 -1.1 2.8 4.4 6.7 5.6 3.3 4.4 6.7
## [433] 7.2 7.2 10.6 7.2 7.8 7.8 5.6 8.3 8.9 7.2 8.9 10.0
## [445] 12.2 14.4 4.4 -0.6 3.3 12.8 6.7 6.1 7.8 12.8 5.6 6.7
## [457] 3.9 8.9 8.9 7.8 9.4 8.9 10.6 9.4 5.6 1.7 3.3 6.1
## [469] 9.4 3.3 1.7 9.4 7.8 11.7 11.7 9.4 8.9 6.1 8.3 7.8
## [481] 3.9 6.1 2.2 0.6 -1.7 0.6 2.8 1.1 10.0 6.7 2.2 3.9
## [493] 3.9 0.0 2.8 6.7 6.7 5.6 4.4 6.1 5.6 5.0 4.4 5.6
## [505] 6.1 3.3 4.4 7.2 9.4 9.4 3.8 4.6 2.9 4.7 0.1 2.2
## [517] 3.1 5.1 5.7 5.6 7.4 5.8 5.4 16.3 18.7 7.2 7.9 7.4
## [529] 6.6 11.9 5.7 9.5 7.8 11.3 7.4 8.2 9.1 10.1 11.9 13.6
## [541] 12.1 12.0 16.0 10.1 1.5 0.6 2.3 1.6 -1.4 2.0 -0.2 3.0
## [553] 2.9 5.1 3.2 4.5 4.8 5.6 6.1 6.1 5.6 7.3 5.7 4.6
## [565] 7.7 6.9 9.3 11.2 13.7 13.2 5.4 6.5 10.0 11.2 8.6 9.9
## [577] 8.7 11.6 10.2 8.1 8.6 7.2 4.5 5.8 5.5 8.5 10.9 6.4
## [589] 5.7 11.2 3.3 4.7 4.9 5.2 4.5 2.1 -4.0 2.8 1.6 0.6
## [601] 0.4 2.0 1.7 3.6 8.9 12.6 10.1 10.0 8.9 8.6 10.7 7.8
## [613] 11.0 10.8 13.8 7.5 6.4 9.2 8.9 4.0 8.9 10.0 9.0 9.9
## [625] 13.5 12.7 14.0 13.8 8.5 8.9 5.6 1.9 5.4 5.5 4.6 5.8
## [637] 6.6 6.7 3.5 5.6 8.5 8.2 7.2 2.4 2.9 11.9 8.5 9.7
## [649] 5.6 8.4 10.7 10.3 8.6 4.1 6.8 2.3 8.0 10.2 11.3 10.3
## [661] 7.7 10.0 11.4 10.5 6.7 6.3 0.4 4.5 13.7 13.3 10.3 16.2
## [673] 20.3 16.2 12.6 6.8 6.6 8.4 7.2 4.2 3.5 2.1 3.3 4.9
## [685] 4.1 9.3 7.6 6.6 10.2 6.7 5.4 7.5 5.6 7.1 7.4 8.5
## [697] 7.2 7.1 8.3 7.8 7.9 6.1 7.5 7.2 6.7 -1.9 -3.3 0.4
## [709] 4.1 8.5 10.0 9.8 13.3 11.5 8.9 9.2 13.5 10.7 9.4 12.5
## [721] 8.0 2.0 2.6 0.5 0.8 4.2 10.3 8.5 8.5 9.6 14.8 10.3
## [733] 7.2 9.9 9.2 15.1 14.8 8.4 9.8 14.6 12.5 4.9 5.1 7.3
## [745] 10.7 11.3 18.6 21.5 9.6 8.9 12.8 12.6 8.6 7.3 5.8 5.9
## [757] 8.1 7.3 9.9 10.7 10.0 14.0 9.3 9.7 8.6 7.1 2.3 5.8
## [769] 8.7 12.3 12.8 16.9 13.9 16.6 18.3 15.0 15.1 13.1 12.2 4.6
## [781] 8.7 5.4 4.9 1.9 6.6 10.3 12.7 13.0 13.8 18.9 15.3 10.7
## [793] 6.6 13.5 9.0 -2.1 -3.9 -3.0 0.4 6.3 2.6 2.1 2.2 0.1
## [805] -1.0 -0.3 5.9 3.3 7.6 10.2 4.5 4.0 6.0 4.0 8.5 6.4
## [817] 6.2 8.2 8.0 7.3 4.7 6.4 7.8 4.1 5.3 9.1 NA NA
## [829] NA NA 12.2 9.2 12.3 10.4 9.1 8.0 7.2 6.5 8.6 8.7
## [841] 1.0 4.6 4.6 6.8 7.6 7.8 9.3 8.9 8.3 9.2 8.4 6.4
## [853] 7.4 7.3 9.3 4.4 5.2 5.9 5.9 7.0 9.8 10.0 9.5 8.5
## [865] 5.5 4.9 6.9 9.7 7.4 5.2 1.4 -0.6 1.0 5.3 8.8 8.2
## [877] 9.1 10.8 9.7 11.1 10.9 12.2 9.4 7.3 9.7 -1.8 -1.1 -0.7
## [889] 0.0 2.1 -1.4 -1.3 3.7 1.8 1.4 2.3 6.2 6.9 5.8 3.8
## [901] 2.7 7.1 5.6 9.9 6.4 8.7 8.6 10.8 12.8 7.3 8.6 8.9
## [913] 8.2 9.4 5.9 5.1 6.3 6.8 8.4 10.2 11.2 9.0 9.8 16.1
## [925] 16.6 19.9 20.8 14.9 14.6 11.1 15.7 14.5 8.8 10.1 8.7 3.3
## [937] 8.0 9.7 11.2 11.7 11.4 10.8 11.6 11.9 10.7 6.8 3.0 1.8
## [949] -0.2 4.5 1.1 4.0 3.9 4.2 -3.4 -7.4 -4.0 -4.7 -4.5 -0.6
## [961] 3.5 5.1 3.2 4.7 4.5 5.4 7.1 6.2 2.6 5.3 7.8 7.4
## [973] 6.4 6.2 8.1 11.7 11.2 NA 8.0 8.2 3.2 6.6 10.4 13.1
## [985] 10.0 7.2 4.9 8.9 8.0 5.6 10.1 9.8 9.4 7.1 7.0 4.8
## [997] 3.2 5.6 7.4 8.7 4.6 5.9 5.7 4.4 4.9 7.1 7.7 6.8
## [1009] 10.8 13.0 12.2 9.8 3.2 6.4 6.9 12.0 13.2 15.2 8.1 8.2
## [1021] 11.9 8.8 7.2 7.9 8.4 6.1 5.8 6.6 4.5 7.8 8.0 9.1
## [1033] 9.2 9.2 10.8 16.7 11.5 10.0 13.0 8.4 6.2 4.2 5.4 6.2
## [1045] 7.5 5.5 10.1 6.6 4.4 4.7 9.5 2.8 6.9 7.3 7.6 7.4
## [1057] 9.5 5.3 8.9 9.6 7.7 10.9 10.6 9.8 7.3 -0.7 0.6 -1.9
## [1069] 7.5 14.6 6.3 3.5 6.5 2.1 6.2 6.8 4.7 6.0 10.6 10.5
## [1081] -2.2 3.6 5.4 6.5 7.6 7.5 2.8 4.3 0.6 2.4 4.1 -3.1
## [1093] 0.5 1.8 2.3 9.1 10.6 5.4 5.0 6.7 8.1 8.8 9.3 7.9
## [1105] 12.5 10.2 1.5 0.5 1.6 2.6 5.5 8.9 10.7 8.5 10.5 6.8
## [1117] 10.9 13.3 17.8 15.5 7.3 9.8 14.9 18.8 13.4 -1.4 0.2 2.0
## [1129] 5.3 7.7 8.8 11.2 7.5 8.0 8.4 10.3 6.9 8.8 9.3 9.2
## [1141] 8.7 11.3 12.8 10.4 6.6 5.2 7.8 7.8 8.8 9.0 10.6 11.1
## [1153] 12.4 12.8 14.6 0.4 4.4 8.3 4.8 7.9 8.1 5.2 7.2 12.3
## [1165] 8.6 0.2 -1.9 -5.0 -2.5 5.2 4.4 6.8 5.9 5.2 6.0 4.1
## [1177] 3.6 3.7 1.9 2.6 3.3 1.9 5.2 5.9 6.2 5.7 6.4 6.6
## [1189] 4.2 2.6 4.5 4.8 2.8 3.5 2.7 4.6 2.0 2.8 3.5 7.2## [1] 1200get 90th from the all year for all day value
## [1] 3.80 3.60 3.70 3.70 3.80 3.90 4.00 4.00 4.04 4.00 4.10 4.10
## [13] 4.12 4.10 4.03 4.22 4.43 4.38 4.27 4.40 4.30 4.30 4.40 4.71
## [25] 4.90 5.00 5.00 5.10 5.37 5.60 5.60 5.80 5.71 5.80 5.70 5.80
## [37] 5.80 5.80 5.90 5.90 5.90 5.80 6.00 6.00 6.10 6.10 6.10 6.31
## [49] 6.52 6.67 6.70 6.70 6.80 7.00 7.20 7.31 7.60 7.80 7.80 7.92
## [61] 7.90 8.20 8.30 8.50 8.58 8.90 9.10 9.40 9.52 9.70 9.90 10.00
## [73] 10.00 10.00 10.20 10.30 10.30 10.40 10.51 10.60 10.60 10.76 10.90 11.10
## [85] 11.21 11.60 11.70 11.90 12.20 12.50 12.80 13.22 13.30 13.50 13.90 14.00
## [97] 14.40 14.40 14.50 14.70 15.00 15.30 15.60 15.80 16.00 16.10 16.20 16.70
## [109] 16.94 17.20 17.50 17.80 18.10 18.30 18.40 18.85 19.00 19.23 19.40 19.50
## [121] 19.69 20.00 20.30 20.60 21.10 21.16 21.70 22.20 22.20 22.20 22.73 22.80
## [133] 23.10 23.28 23.30 23.30 23.30 23.30 23.30 23.40 23.90 23.90 23.90 24.00
## [145] 24.20 24.30 24.40 24.40 24.50 24.60 24.80 24.90 25.00 25.00 25.10 25.00
## [157] 25.00 25.00 25.00 25.20 25.20 25.30 25.40 25.60 25.60 25.70 25.80 25.90
## [169] 26.00 26.10 26.10 26.10 26.20 26.28 26.33 26.60 26.70 26.70 26.70 26.70
## [181] 26.70 26.70 26.90 26.90 27.20 27.20 27.50 27.55 27.50 27.40 27.40 27.39
## [193] 27.40 27.51 27.80 27.80 27.90 28.10 28.10 28.10 28.10 28.30 28.34 28.60
## [205] 28.90 29.10 29.10 29.17 29.20 29.10 29.30 29.29 29.29 29.20 29.30 29.20
## [217] 29.20 29.20 28.99 28.90 28.90 28.90 28.90 28.70 28.68 28.60 28.50 28.30
## [229] 28.20 28.10 27.90 27.80 27.50 27.20 26.80 26.70 26.10 25.94 25.73 25.60
## [241] 25.30 25.00 24.80 24.70 24.80 24.70 24.60 24.60 24.40 24.40 24.40 24.40
## [253] 24.16 23.90 23.76 23.30 23.30 23.30 23.30 23.00 22.96 22.80 22.80 22.80
## [265] 22.40 22.20 21.96 21.70 21.70 21.66 21.56 21.16 20.60 20.10 19.66 19.30
## [277] 18.90 18.90 18.44 18.30 18.30 18.00 17.80 17.20 17.00 16.70 16.60 16.10
## [289] 15.80 15.60 15.00 14.60 14.40 14.20 13.90 13.70 13.50 13.30 12.90 12.80
## [301] 12.40 12.20 12.20 11.70 11.19 10.60 10.54 10.19 10.00 10.00 9.40 9.32
## [313] 8.90 8.60 8.30 8.06 7.80 7.70 7.60 7.20 7.20 6.80 6.70 6.70
## [325] 6.30 6.20 6.10 6.10 5.95 5.90 5.70 5.60 5.60 5.36 5.00 5.00
## [337] 4.60 4.40 4.50 4.40 4.50 4.50 4.40 4.40 4.40 4.40 4.40 4.40
## [349] 4.40 4.40 4.40 4.40 4.40 4.40 4.40 4.40 4.40 4.40 4.26 4.20
## [361] 4.20 4.20 3.90 3.90 3.90 3.90Plot
plot given year temp dist vs baseline 90th
## `summarise()` has grouped output by 'Month'. You can override using the
## `.groups` argument.## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
plot all year temp in grey vs baseline
## Warning: Removed 468 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 466 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 468 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 466 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Warning: Removed 467 rows containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
## Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
Analyze the hw
hw dist for certain 1 year
prepare for the data
## # A tibble: 20 × 7
## Month Day Percentile_90 MAX_TEMP_YEAR DayOfYear Condition Cumulative_Count
## <int> <int> <dbl> <dbl> <dbl> <lgl> <dbl>
## 1 1 11 4.1 5.5 11 TRUE 1
## 2 1 12 4.1 5.5 12 TRUE 2
## 3 3 17 10.3 11.2 76 TRUE 1
## 4 3 18 10.4 12.1 77 TRUE 2
## 5 3 19 10.5 14 78 TRUE 3
## 6 3 20 10.6 15.7 79 TRUE 4
## 7 3 21 10.6 15.7 80 TRUE 5
## 8 3 22 10.8 14.5 81 TRUE 6
## 9 5 9 22.2 25 129 TRUE 1
## 10 5 10 22.7 25.1 130 TRUE 2
## 11 5 11 22.8 26 131 TRUE 3
## 12 5 27 24.4 26.6 147 TRUE 1
## 13 5 28 24.5 27.7 148 TRUE 2
## 14 5 29 24.6 26.5 149 TRUE 3
## 15 5 30 24.8 27.1 150 TRUE 4
## 16 5 31 24.9 27.4 151 TRUE 5
## 17 6 12 25.6 26.4 163 TRUE 1
## 18 9 3 24.6 25.6 246 TRUE 1
## 19 11 17 6.8 11.9 321 TRUE 1
## 20 11 24 5.95 6.3 328 TRUE 1plot hw analysis for all year
plot overall count of hw through years
## Case_Length Count Year
## 1 4 1 1942
## 2 5 1 1942
## 3 3 2 1943
## 4 4 1 1943
## 5 3 1 1944
## 6 4 1 1944
## 7 5 1 1944
## 8 3 2 1945
## 9 4 1 1945
## 10 3 2 1946
## 11 4 1 1946
## 12 5 1 1946
## 13 4 2 1947
## 14 6 1 1947
## 15 4 1 1948
## 16 5 1 1948
## 17 3 1 1949
## 18 4 2 1949
## 19 8 1 1949
## 20 3 2 1950
## 21 9 1 1950
## 22 3 3 1951
## 23 4 1 1951
## 24 3 3 1952
## 25 5 1 1952
## 26 3 1 1953
## 27 6 1 1953
## 28 3 1 1954
## 29 4 2 1954
## 30 3 1 1955
## 31 3 2 1956
## 32 4 1 1956
## 33 5 1 1956
## 34 3 1 1957
## 35 3 5 1958
## 36 4 2 1958
## 37 5 1 1958
## 38 6 1 1958
## 39 8 1 1958
## 40 4 1 1959
## 41 3 3 1960
## 42 3 4 1961
## 43 4 1 1961
## 44 6 1 1961
## 45 3 1 1962
## 46 4 1 1962
## 47 5 1 1962
## 48 6 1 1962
## 49 3 1 1963
## 50 4 1 1963
## 51 6 1 1963
## 52 3 1 1964
## 53 3 3 1965
## 54 4 1 1965
## 55 3 2 1966
## 56 4 2 1967
## 57 3 1 1968
## 58 4 1 1968
## 59 6 1 1968
## 60 7 1 1968
## 61 3 1 1969
## 62 4 1 1969
## 63 5 3 1969
## 64 6 1 1969
## 65 3 4 1970
## 66 3 2 1971
## 67 4 1 1971
## 68 3 1 1972
## 69 4 1 1972
## 70 3 2 1973
## 71 6 1 1973
## 72 3 2 1975
## 73 5 1 1975
## 74 3 2 1976
## 75 3 1 1977
## 76 5 2 1977
## 77 3 1 1978
## 78 4 2 1978
## 79 3 6 1979
## 80 4 1 1979
## 81 5 2 1979
## 82 3 2 1980
## 83 4 2 1980
## 84 5 2 1980
## Case_Length Count Year
## 1 3 2 1980
## 2 4 2 1980
## 3 5 2 1980
## 4 3 2 1981
## 5 4 3 1981
## 6 5 1 1981
## 7 6 1 1981
## 8 3 1 1982
## 9 4 3 1982
## 10 4 1 1983
## 11 5 1 1983
## 12 3 3 1984
## 13 4 1 1984
## 14 5 1 1984
## 15 3 1 1985
## 16 4 1 1985
## 17 3 4 1986
## 18 4 1 1986
## 19 7 1 1986
## 20 3 7 1987
## 21 5 2 1987
## 22 3 3 1988
## 23 4 1 1988
## 24 5 1 1988
## 25 3 3 1989
## 26 3 2 1990
## 27 4 1 1990
## 28 4 1 1991
## 29 5 2 1991
## 30 7 2 1991
## 31 3 5 1992
## 32 5 3 1992
## 33 6 1 1992
## 34 3 2 1993
## 35 4 2 1993
## 36 3 2 1994
## 37 8 2 1994
## 38 3 6 1995
## 39 5 1 1995
## 40 4 1 1996
## 41 3 1 1997
## 42 4 1 1997
## 43 5 1 1997
## 44 3 1 1998
## 45 4 1 1998
## 46 5 2 1998
## 47 3 3 1999
## 48 4 2 2001
## 49 3 1 2002
## 50 4 2 2002
## 51 5 1 2002
## 52 3 2 2003
## 53 4 1 2003
## 54 7 1 2003
## 55 3 1 2004
## 56 4 1 2004
## 57 9 2 2004
## 58 3 3 2005
## 59 4 1 2005
## 60 5 2 2005
## 61 7 2 2005
## 62 9 1 2005
## 63 3 3 2006
## 64 5 1 2006
## 65 6 1 2006
## 66 8 1 2006
## 67 3 1 2007
## 68 4 2 2007
## 69 3 3 2008
## 70 4 2 2008
## 71 3 2 2009
## 72 4 1 2009
## 73 9 1 2009
## 74 3 2 2010
## 75 4 1 2010
## 76 6 2 2010
## 77 4 2 2012
## 78 3 4 2013
## 79 5 1 2013
## 80 3 4 2014
## 81 4 1 2014
## 82 3 3 2015
## 83 5 1 2015
## 84 6 1 2015
## 85 3 1 2016
## 86 6 1 2016
## 87 11 1 2016
## 88 3 1 2017
## 89 4 1 2017
## 90 5 1 2017
## 91 3 3 2018
## 92 4 4 2018
## 93 5 1 2018
## 94 3 1 2019
## 95 5 1 2019
## 96 6 1 2019
## 97 5 1 2020
## 98 3 2 2021
## 99 7 1 2021
## 100 3 3 2022
## 101 5 2 2022
## 102 6 2 2022
## 103 3 5 2023
## 104 4 3 2023
## 105 9 1 2023
## 106 5 1 2024
## 107 7 1 2024plot for heat map
examine specific year
## Warning: Removed 466 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 2 rows containing missing values or values outside the scale range
## (`geom_line()`).## Warning: Removed 1 row containing missing values or values outside the scale range
## (`geom_line()`).
